Business and consumer records are typically contained in databases and other forms of data repositories. Typical databases may contain records such as demographic data, customer data, marketing data, name and address information, observed and self-reported lifestyle and other behavioral data, consumer data, public record information, realty and property tax information, summarized automotive statistics, summarized financial data, census data, and so on. Virtually any type of information may be contained in any such database. One such highly inclusive database, containing much of the above-mentioned types of data for approximately 98% of U.S. individuals and living units (households), is the Experian INSOURCE® database.
Various database applications have been directed to attempts to utilize the wide array of information contained in such databases for marketing and analytical purposes. For example, demographic data may be appended to customer records, to identify the demographic composition of a set of customers, followed by marketing directed toward people having similar demographic characteristics.
These database applications, in their various forms, attempt to understand and access distinct customer and prospect groups, and then send the right message to the right individual, household, living unit or other target audience. Typically, all of the individuals and/or households contained in the corresponding database are segmented into groups which share distinct demographic, lifestyle, and consumer behavior characteristics. In other applications, following such segmentation, consumer attitudes and motivations are assumed and attributed to those individuals/households within each such segment or cluster. The number of segments utilized varies widely by application.
In addition, in these various database marketing applications, consumer attitudes and preferred marketing message themes or types are generally assumed and assigned to a segment, without any independent empirical research and analysis. As a consequence, once a population is segmented, any further analysis of the population based on preferred messaging themes does not, in fact, add any additional, independent information, and merely reiterates the underlying message theme assumptions of any given segment.
The resulting data, moreover, may have a large degree of uncertainty, may or may not be accurate, and may or may not be actionable. For example, the attitudes, motivations and behaviors attributed or assigned to each segment may not be accurate and may not be based on factual, empirical research. Such attitudes, motivations and behaviors may or may not actually reflect representative attitudes found in a particular customer database.
The diminished accuracy of current marketing methods is further underscored by comparatively low response rates, such as 1-2% response from a target audience for direct mail marketing. Other methods and systems are required to appropriately target and motivate the remainder of the target audience, and to determine potentially new and underdeveloped target audiences. In addition, new methods and systems are required to maximize marketing returns, by not overly saturating the target audience with excessive and ineffective communications, and instead to appropriately communicate with the target audience using the audience's preferred methods and times of communication.
As a consequence, a need remains for a predictive methodology and system, for accurate prediction of attitudes, motivations and behaviors, which may be utilized for marketing applications. Such a method and system should be empirically-based, such as based on actual attitudinal, behavioral or demographic research and other information from a population sample, and further should provide accurate modeling to predict and extrapolate such attitudinal or other information to a larger or entire population. Such a method and system should provide information concerning preferred message themes or message content independently from any population grouping, segmentation or clustering process. In addition, such a method and system should be actionable, providing not only audience attitudinal information and preferred message content, but also preferred communication channel information or other preferred communication media, preferred frequency of communication or other contact, and communication timing information.